@Article{SánchezGácitaLonFreFreMar:2017:ImMiSt,
author = "S{\'a}nchez G{\'a}cita, Madeleine and Longo, Karla Maria and
Freire, Juliana Larise Mendon{\c{c}}a and Freitas, Saulo Ribeiro
de and Martin, Scot T.",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Harvard University}",
title = "Impact of mixing state and hygroscopicity on CCN activity of
biomass burning aerosol in Amazonia",
journal = "Atmospheric Chemistry and Physics",
year = "2017",
volume = "17",
number = "3",
pages = "2373--2392",
month = "Feb.",
abstract = "Smoke aerosols prevail throughout Amazonia because of widespread
biomass burning during the dry season, and external mixing, low
variability in the particle size distribution and low particle
hygroscopicity are typical. There can be profound effects on cloud
properties. This study uses an adiabatic cloud model to simulate
the activation of smoke particles as cloud condensation nuclei
(CCN) for three hypothetical case studies, chosen as to resemble
biomass burning aerosol observations in Amazonia. The relative
importance of variability in hygroscopicity, mixing state, and
activation kinetics for the activated fraction and maximum
supersaturation is assessed. For a population with kappa(p) = 0.04
an overestimation of the cloud droplet number concentration N d
for the three selected case studies between 22.4 +/- 1.4 and 54.3
+/- 3.7% was obtained when assuming a hygroscopicity parameter
kappa(p) = 0.20. Assuming internal mixing of the aerosol
population led to overestimations of up to 20% of N d when a group
of particles with medium hygroscopicity was present in the
externally mixed population cases. However, the overestimations
were below 10% for external mixtures between very low and
low-hygroscopicity particles, as seems to be the case for Amazon
smoke particles. Kinetic limitations were significant for
medium-and high-hygroscopicity particles, and much lower for very
low and low-hygroscopicity particles. When particles were assumed
to be at equilibrium and to respond instantly to changes in the
air parcel supersaturation, the overestimation of the droplet
concentration was up to similar to 100% in internally mixed
populations, and up to similar to 250% in externally mixed ones,
being larger for the higher values of hygroscopicity. In addition,
a perceptible delay between the times when maximum supersaturation
and maximum aerosol activated fraction are reached was noticed
and, for aerosol populations with effective hygroscopicity
kappa(Peff) higher than a certain threshold value, the delay in
particle activation was such that no particles were activated at
the time of maximum supersaturation. Considering internally mixed
populations, for an updraft velocity W = 0.5 m s(-1) this
threshold of no activation varied between kappa(Peff) = 0.35 and
kappa(Peff) = 0.5 for the different case studies. However, for low
hygroscopicity, kinetic limitations played a weaker role for CCN
activation of particles, even when taking into account the large
aerosol mass and number concentrations. For the very low range of
hygroscopicities, the overestimation of the droplet concentration
due to the equilibrium assumption was lowest and the delay between
the times when maximum supersaturation and maximum activated
fraction were reached was greatly reduced or no longer observed
(depending on the case study). These findings on uncertainties and
sensitivities provide guidance on appropriate simplifications that
can be used for modeling of smoke aerosols within general
circulation models. The use of medium values of hygroscopicity
representative of smoke aerosols for other biomass burning regions
on Earth can lead to significant errors compared to the use of low
hygroscopicity for Amazonia (between 0.05 and 0.13, according to
available observations). Also in this region, consideration of the
biomass burning population as internally mixed will lead to small
errors in the droplet concentration, while significantly
increasing the computational burden.",
doi = "10.5194/acp-17-2373-2017",
url = "http://dx.doi.org/10.5194/acp-17-2373-2017",
issn = "1680-7316 and 1680-7324",
language = "en",
targetfile = "sanchez_impact.pdf",
urlaccessdate = "23 abr. 2024"
}